Cross-validation for time series

December 5, 2016

(This article was originally published at Hyndsights on Rob J Hyndman, and syndicated at StatsBlogs.)

I’ve added a couple of new functions to the forecast package for R which implement two types of cross-validation for time series.K-fold cross-validation for autoregression The first is regular k-fold cross-validation for autoregressive models. Although cross-validation is sometimes not valid for time series models, it does work for autoregressions, which includes many machine learning approaches to time series. The theoretical background is provided in Bergmeir, Hyndman and Koo (2015). So cross-validation can be applied to any model where the predictors are lagged values of the response variable.

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